Transcriptome landscape of high and low responders to an inactivated COVID-19 vaccine after 4 months using single-cell sequencing (preprint)

BackgroundVariability in antibody responses among individuals following vaccination is a universal phenomenon. Single-cell transcriptomics offers a potential avenue to understand the underlying mechanisms of these variations and improve our ability to evaluate and predict vaccine effectiveness. ObjectiveThis study aimed to explore the potential of single-cell transcriptomic data in understanding the variability of antibody responses post-vaccination and its correlation with transcriptomic changes. MethodsBlood samples were collected from 124 individuals on day 21 post COVID-19 vaccination. These samples were categorized based on antibody titers (high, medium, low). On day 135, PBMCs from 27 donors underwent single-cell RNA sequencing to depict the transcriptome atlas. ResultsDifferentially expressed genes (DEGs) affecting antibody expression in various cell types were identified. We found that innate immunity, B cell, and T cell population each had a small set of common DEGs (MT-CO1, HLA-DQA2, FOSB, TXNIP, and JUN), and Macrophages and Th1 cells exhibited the largest number of DEGs. Pathway analysis highlighted the dominant role of the innate immune cell population in antibody differences among populations, with a significant impact from the interferon pathway. Furthermore, protein complexes analysis revealed that alterations in the ribosome complex, primarily regulated by DC cells, may play a crucial role in regulating antibody differences. Combining these findings with previous research we proposed a potential regulatory mechanism model of DC cells on B cell antibody production. ConclusionWhile direct prediction of specific antibody levels using single-cell transcriptomic data remains technically and data-wise challenging, our study demonstrated the vast potential of single-cell transcriptomics in understanding the mechanisms underlying antibody responses induced by vaccines.

Manifestations and outcomes of intracerebral hemorrhage during COVID‐19 pandemic in China: a multicenter, longitudinal cohort study (preprint)

Background: We just right were carrying out a multicenter cohort study about ICH when COVID-19 broke out in Wuhan，and we wondered whether COVID-19 pandemic was associated with the manifestations and outcomes of intracerebral hemorrhage (ICH). Methods: : Acute ICH patients before (1/12/2018-30/11/2019) and during COVID-19(1/12/2019-30/11/2020) pandemic at 31 centers in China, were entered into the analysis. Demographic information, clinical manifestations and outcomes were collected and compared between the two groups. Results: : From December 1, 2018 to November 30, 2020, a total of 3460 patients with ICH were enrolled and eventually analyzed. Results showed that patients with ICH were more likely to be older, have higher systolic blood pressure (BP) (P<0.001), diastolic-BP (P=0.002), higher admission NIHSS score (P=0.039) and higher fasting blood glucose (P=0.003) during COVID-19 pandemic compared with before. After adjusting age, gender, COVID-19 pandemic was associated with 3-month poor outcome (OR = 1.206, 95%CI: 1.043-1.395) and 3-month mortality (OR = 1.711, 95%CI: 1.428-2.050) after ICH onset. Conclusions: : COVID-19 pandemic deteriorated the manifestations and outcomes of ICH.

Discovery of orally active SARS-CoV-2 papain-like protease (PLpro) inhibitors (preprint)

Vaccines and first-generation antiviral therapeutics have provided important protection against coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there remains a need for additional therapeutic options that provide enhanced efficacy and protection against potential viral resistance. The SARS-CoV-2 papain-like protease (PLpro) is one of two essential cysteine proteases involved in viral replication. While inhibitors of the SARS-CoV-2 main protease (Mpro) have demonstrated clinical efficacy, known PLpro inhibitors have to date lacked the inhibitory potency and requisite pharmacokinetics to demonstrate that targeting PLpro translates to in vivo efficacy in a preclinical setting. Herein, we report the machine learning-driven discovery of potent, selective, and orally available SARS-CoV-2 PLpro inhibitors, with lead compound PF-07957472 (4) providing robust efficacy in a mouse-adapted model of COVID-19 infection.

Comparison of respiratory pathogens in children with community-acquired pneumonia before and during the COVID-19 Pandemic (preprint)

Background Multifaceted non-pharmaceutical interventions during the COVID-19 pandemic have not only reduced the transmission of SARS-CoV2, but have had an effect on the prevalence of other pathogens. This retrospective study aimed to compare and analyze the changes of respiratory pathogens in hospitalized children with community-acquired pneumonia.Methods From January 2019 to December 2020, children with community-acquired pneumonia were selected from the Department of Respiratory Medicine, Shanghai Children's Medical Center. On the first day of hospitalization, sputum, throat swabs, venous blood samples from them were collected for detection of pathogens.Results A total of 2596 children with community-acquired pneumonia were enrolled, including 1871 patients in 2019 and 725 in 2020. The detection rate in 2020 was lower than in 2019, whether single or multiple pathogens. Compared with 2019, the detection rate of virus, especially parainfluenza virus, influenza virus and respiratory syncytial virus, all decreased in 2020. On the contrary, the prevalence of human rhinovirus was much higher than that in 2019. In addition, the positivity rate for bacteria did not change much over the two years, which seemed to be less affected by COVID-19. And Mycoplasma pneumoniae which broke out in 2019 has been in low prevalence since March 2020 even following the reopening of school.Conclusions Strict public health interventions for COVID-19 in China have effectively suppressed the spread of not only SARS-CoV2 but parainfluenza virus, influenza virus and Mycoplasma pneumonia as well. However, it had a much more limited effect on bacteria and rhinovirus. Therefore, more epidemiological surveillance of respiratory pathogens will help improve early preventive measures.

Evaluation on the Specificity and Sensitivity of a COVID-19 and A+B Influenza Antigen Combo Test for Detection and Application in Rapid Chromatographic Immunoassays

[...]fecal-oral transmission, where rotavirus is present in the feces of a patient is excreted and often contaminates water, food, clothing, toys, utensils, and other high touch objects. When a healthy person comes into contact with these items, the virus can enter the body through the hand or mouth and cause lesions in the digestive tract [4, 7]. Since 2019, the spread of COVID-19 has posed a public health threat throughout the world, endangering people's lives. According to research, N95 masks are more protective against COVID-19 than normal masks. Limiting aggregation is also an important means to limit the spread of the viruses. [...]control measures to limit the number of people gathering and intervening in public places are effective [7].

Development of Highly Potent Noncovalent Inhibitors of SARS-CoV-2 3CLpro

The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, noncovalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. A novel oral noncovalent inhibitor of 3C-like protease, named WU-04, was developed as a promising drug candidate for COVID-19 treatment.

Significance of SARS-CoV-2 and Influenza A+B Antigen Combo Rapid Test for Distinguishing Influenza from COVID-19

According to the Centers for Disease Control (CDC), typical flu symptoms include fever, cough, sore throat, muscle aches, headache, runny or stuffy nose, fatigue, and sometimes even vomiting and diarrhea [1]. Healthcare providers should follow the Centers for Disease Control and Prevention (CDC) recommendations for infection control and the appropriate use of personal protective equipment [5]. Because some of the symptoms of influenza and COVID-19 are similar, it may be difficult to distinguish between the two respiratory diseases based on symptoms alone. [...]it is necessary to test for both viruses in anyone with symptoms of COVID-19 or influenza. [...]after the test is completed, place all the components into the plastic bag and tightly seal and dispose of according

Cost-effectiveness of the second COVID-19 booster vaccination in the United States (preprint)

ABSTRACT Background: On March 29, 2022, the United States (US) authorized the second booster dose of COVID-19 vaccine for individuals aged 50 years and older. To date, the cost-effectiveness of the second booster strategy remains unassessed. Methods: We developed a decision-analytic SEIR-Markov model by five age groups (0-4yrs with 18,827,338 individuals, 5-11yrs with 28,584,443 individuals, 12-17yrs with 26,154,652 individuals, 18-49yrs with 138,769,369 individuals, and 50+yrs with 119,557,943 individuals) to evaluate the cost-effectiveness of the second COVID-19 booster vaccination (administered 4 months after the first booster dose) over an evaluation period of 180 days in the US, from a healthcare system perspective. Results: Implementing the second booster strategy among individuals aged 50+ years would cost US$807 million but reduce direct medical care costs by $1,128 million, corresponding to a benefit-cost ratio of 1.40. This strategy would also result in a gain of 1,048 QALYs during the 180 days, indicating it was cost-saving. Probabilistic sensitivity analysis demonstrated that the probability of being cost-effective with the strategy was 68%. Further, vaccinating individuals aged 18-49 years with the second booster would result in an additional gain of $1,566 million and 2,276 QALYs. Expanding vaccination to individuals aged 12-17 years would result in an additional gain of $15 million and 89 QALYs. Coverage of the first booster vaccination in age groups under 12 was too low to consider the administration of the second booster. If the social interaction between all age groups was severed, vaccination expansion to 18-49yrs and 12-17yrs would no longer be cost-effective. Conclusion: The second booster strategy was likely to be effective and cost-effective in reducing the disease burden of the COVID-19 pandemic. Expanding the second booster strategy to 18-49yrs and 12-17yrs remains cost-effective due to their social contacts with the older age group. Keywords: COVID-19; Second booster; Cost-effective analysis; SEIR-Markov model; Age groups

New-Onset Diabetes and COVID-19: Evidence from a Global Clinical Registry (preprint)

Background Mounting evidence shows association between COVID-19 and new diagnoses of diabetes. It is unclear, however, if COVID-19 increases detection of pre-existing diabetes or if it can induce new-onset of the disease. Methods We established a global online registry of COVID-19-related diabetes (CoviDIAB) using a web-enabled data capture system (Dendrite Clinical Systems). In this study we aimed to investigate whether COVID-19 can induce new-onset diabetes, its subtypes and clinical manifestations. To this end, we analyzed clinical and laboratory data from cases of newly-diagnosed diabetes occurring during or within four weeks from an episode of COVID-19. To exclude pre-existing hyperglycaemia, new-onset diabetes was defined as: blood sugar levels above diabetes thresholds (fasting glycaemia ≥ 126 mg/dL or non-fasting glycemia > 200 mg/dL), no prior history of the disease or use of glucose-lowering medications, and HbA1c < 6·5% at presentation. Results Between October 2020 and April 2022, 67 contributors from 61 hospitals in 25 countries entered data on 537 eligible cases of newly-diagnosed diabetes. New-onset diabetes was identified in 102 of 473 newly-diagnosed cases with recorded HbA1c (22%). Among adults, diabetes subtypes were type 2 (59%) and “not-yet known” (41%). There were two cases of new-onset type 1 diabetes among children. Hyperglycaemia persisted beyond resolution of the infection in 39 of 89 (45%) patients with new-onset diabetes who survived the episode of COVID-19. Further follow-up data beyond 3-months was available for 28 such cases, showing remission of diabetes in five and persistent diabetes in 23 cases (82%). Conclusions This study shows clinical plausibility for a diabetogenic effect of COVID-19, supporting screening for diabetes in people who contract the infection. Further investigation is warranted to confirm mechanisms of viral interference with glucose metabolism. The CoviDIAB registry is accessible online at http://covidiab.e-dendrite.com.

Massive airway hemorrhage in severe COVID-19 and the role endotracheal tube clamping (preprint)

Background Venovenous extracorporeal membrane oxygenation (VV-ECMO) has been widely used in treating patients with coronavirus disease 2019 (COVID-19) with severe respiratory failure. However, there are few reports of the successful treatment of patients with massive airway hemorrhage in severe COVID-19 during VV-ECMO treatment.Methods We analyzed the treatment process of a patient with massive airway hemorrhage in severe COVID-19, who underwent prolonged VV-ECMO treatment.Results A 59-year-old female patient was admitted to the intensive care unit after confirmed severe acute respiratory syndrome coronavirus 2 infection with severe acute respiratory distress syndrome. VV-ECMO, mechanical ventilation and prone ventilation were administered. Major airway hemorrhage occurred on day 14 of ECMO treatment; conventional management was ineffective. We provided complete VV-ECMO support, discontinued anticoagulation, disconnected the ventilator, clipped the tracheal intubation, and intervened to embolize the descending bronchial arteries. After the pulmonary pemorrhage stopped, we administered cryotherapy under bronchoscopy, low-dose urokinase locally, and bronchoalveolar lavage in the airway to clear the blood clots. The patient’s condition gradually improved; she underwent ECMO weaning and decannulation after 88 days of VV-ECMO treatment, and the membrane oxygenator was changed out four times. She was successfully discharged after 182 days in hospital.Conclusion Massive airway hemorrhage in patients with severe COVID-19 and treated with ECMO is catastrophic. It is feasible to clamp the tracheal tube with the full support of ECMO. Notably, bronchoscopy with cryotherapy is effective for removing blood clots.

A Web Knowledge-Driven Multimodal Retrieval Method in Computational Social Systems: Unsupervised and Robust Graph Convolutional Hashing

Multimodal retrieval has received widespread consideration since it can commendably provide massive related data support for the development of computational social systems (CSSs). However, the existing works still face the following challenges: 1) rely on the tedious manual marking process when extended to CSS, which not only introduces subjective errors but also consumes abundant time and labor costs;2) only using strongly aligned data for training, lacks concern for the adjacency information, which makes the poor robustness and semantic heterogeneity gap difficult to be effectively fit;and 3) mapping features into real-valued forms, which leads to the characteristics of high storage and low retrieval efficiency. To address these issues in turn, we have designed a multimodal retrieval framework based on web-knowledge-driven, called unsupervised and robust graph convolutional hashing (URGCH). The specific implementations are as follows: first, a "secondary semantic self-fusion" approach is proposed, which mainly extracts semantic-rich features through pretrained neural networks, constructs the joint semantic matrix through semantic fusion, and eliminates the process of manual marking;second, a "adaptive computing" approach is designed to construct enhanced semantic graph features through the knowledge-infused of neighborhoods and uses graph convolutional networks for knowledge fusion coding, which enables URGCH to sufficiently fit the semantic modality gap while obtaining satisfactory robustness features;Third, combined with hash learning, the multimodality data are mapped into the form of binary code, which reduces storage requirements and improves retrieval efficiency. Eventually, we perform plentiful experiments on the web dataset. The results evidence that URGCH exceeds other baselines about 1%-3.7% in mean average precisions (MAPs), displays superior performance in all the aspects, and can meaningfully provide multimodal data retrieval services to CSS.

Prolonged Viral Shedding in Three Young Adult Cases of COVID-19

Severe acute respiratory syndrome coronavirus-2 infection is usually self-limited, with a short duration for viral shedding within several weeks. However, prolonged viral shedding has been observed in severe or immune-compromised coronavirus disease 2019 (COVID-19) cases. Here, we reported that three young adult cases of COVID-19 patients, who were either immunosuppressed nor severe, showed prolonged viral RNA shedding from the upper respiratory tract for 58, 81, and 137 days since initial diagnosis. To our knowledge, this is the longest duration of viral shedding reported to date in young adult patients. Further studies on factors relevant to prolonged viral positivity, as well as the correlation between viral positivity and transmission risk are needed for the optimal management of COVID-19 patients with prolonged nucleic acid positive.

Quantifying social interventions in combating COVID-19 via a symmetry-based model (preprint)

The COVID-19 pandemic reveals new features of substantial changes in rates of infection, cure, and death, resulting from social intervention, which significantly challenges traditional SEIR-type models. This paper develops a symmetry-based model for quantifying social interventions in combating COVID-19. We find three key order parameters, separating degree (S) for susceptible populations, healing degree (H) for mild cases, and rescuing degree (R) for server cases, all display logistic dynamics, which establish a novel dynamic model named SHR. Furthermore, we discover two evolutionary patterns of healing degree with a universal power law in 23 areas in the first wave. Remarkably, the model yields a quantitative evaluation of the ‘dynamic back-to-zero’ policy in the third wave in Beijing by 12 datasets of different sizes. In conclusion, the SHR model constitutes a rational basis to understand this complex epidemic, and for policymakers to carry out sustainable anti-epidemic measures to minimize its impact.

Investigation of a cluster of COVID-19 cases imported through inbound air flight

Objective: To understand the epidemiological characteristics and explore source of infection of coronavirus disease 2019 (COVID-19) cases imported through an inbound air flight from Kenya to Guangzhou, China.

Therapeutic prospects of ceRNAs in COVID-19

Since the end of 2019, COVID-19 caused by SARS-CoV-2 has spread worldwide, and the understanding of the new coronavirus is in a preliminary stage. Currently, immunotherapy, cell therapy, antiviral therapy, and Chinese herbal medicine have been applied in the clinical treatment of the new coronavirus;however, more efficient and safe drugs to control the progress of the new coronavirus are needed. Long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) may provide new therapeutic targets for novel coronavirus treatments. The first aim of this paper is to review research progress on COVID-19 in the respiratory, immune, digestive, circulatory, urinary, reproductive, and nervous systems. The second aim is to review the body systems and potential therapeutic targets of lncRNAs, miRNAs, and circRNAs in patients with COVID-19. The current research on competing endogenous RNA (ceRNA) (lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA) in SARS-CoV-2 is summarized. Finally, we predict the possible therapeutic targets of four lncRNAs, MALAT1, NEAT1, TUG1, and GAS5, in COVID-19. Importantly, the role of PTEN gene in the ceRNA network predicted by lncRNA MALAT1 and lncRNA TUG1 may help in the discovery and clinical treatment of effective drugs for COVID-19.

Clinical analysis on clinical value of initial chest CT findings in patients with COVID-19

Objective: To assess the clinical value of initial chest CT findings in patients with COVID-19.

Effects of different mucosal adjuvants on the immune responses induced by porcine deltacoronavirus in mice

Objective: The aim of this study is to screen an ideal adjuvant for an inactivated porcine deltacoronavirus(PDCoV) vaccine to induce mucosal immunity and reduce the side effect of the vaccine. We used different mucosal adjuvants to prepare the inactivated PDCoV vaccines. We then used mouse model to evaluate the humoral, cellular and mucosal immune responses induced by the inactivated vaccines via different immunization routes.